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pith:CH5V77TW

pith:2026:CH5V77TW4BFNHBEX7ACUJVQKY4
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HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation

Edward Ajayi, Prasenjit Mitra

Cognitive personas synthesizing humor data let a 7B model match or beat much larger LLMs at comedy.

arxiv:2604.09629 v2 · 2026-03-19 · cs.CL

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3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

our 7B model significantly outperforms larger instruction-tuned baselines and achieves performance competitive with state-of-the-art proprietary models. We find that cognitive-driven data curation is far more critical than alignment algorithms or model scale for humor generation.

C2weakest assumption

The humor data synthesized using the six cognitive personas through the Mixture-of-Thought approach provides a high-quality, diverse training signal that effectively improves the model's humor generation capabilities beyond what standard methods achieve.

C3one line summary

A 7B LLM fine-tuned on humor data generated via six cognitive personas and Mixture-of-Thought outperforms larger instruction-tuned baselines and competes with proprietary models.

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Receipt and verification
First computed 2026-05-29T01:05:09.218698Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

11fb5ffe76e04ad38497f80544d60ac73f0b103bce0d44165748bf69ec58a0f3

Aliases

arxiv: 2604.09629 · arxiv_version: 2604.09629v2 · doi: 10.48550/arxiv.2604.09629 · pith_short_12: CH5V77TW4BFN · pith_short_16: CH5V77TW4BFNHBEX · pith_short_8: CH5V77TW
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CH5V77TW4BFNHBEX7ACUJVQKY4 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 11fb5ffe76e04ad38497f80544d60ac73f0b103bce0d44165748bf69ec58a0f3
Canonical record JSON
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    "cross_cats_sorted": [],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-03-19T13:12:53Z",
    "title_canon_sha256": "a70fe9a889fc1b56c29469a1aecb5c4cec6f569778a619b78ca907d659a852eb"
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